Frequency Regulation of Electric Vehicle-Penetrated Power System Using MPA-Tuned New Combined Fractional Order Controllers

Abstract

Energy transition from traditional generation sources into new renewable energy generation has become essential for facing climate changes. However, increased penetration levels of renewable energy sources (RESs) make power systems subjected to low inertia problems. Moreover, the continuously growing numbers of electric vehicles (EVs) have made the substantial need for their contribution in power systems. Therefore, this paper proposes a combined fractional-order controller using the parallel combination of tiltintegral-derivative with filter (TIDF) and hybrid fractional-order (HybFO) controllers for robust frequency regulation in interconnected power systems. The proposed controller is advantageous in combining the merits of two fractional-order controllers that result in more robust and effective load frequency control (LFC) at wide range and different types of disturbances. Furthermore, a new application of marine predator optimization algorithm (MPA) is proposed for simultaneously determining the optimum controller parameters in the different power system areas. The existing EVs contribute in performing additional functionality in power systems. EVs help in damping out the frequency and tie-line power oscillations in the proposed work. The two-area interconnected power system is selected as a case study with the installed photovoltaic (PV), and wind generations in addition to distributed EVs among areas. The obtained results show the superiority and suitability of the proposed controller over the traditional controllers in the literature. Additionally, the effectiveness of the MPA is validated and compared with recent meta-heuristic optimization algorithms.INDEX TERMS Electric vehicles (EVs), interconnected power systems, load frequency control (LFC), marine predator optimization algorithm (MPA), renewable energy sources (RESs).

Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control

“…On the other hand, research relating to controllers have yet to reach a single consensus. According to the recent work of [22], most controllers fall under an integral order, fractional order, intelligent, or cascaded structure. Of which, fractional order and intelligent controllers have been focused.…”

“…Fractional order controllers have been gaining attention with the added ability to better tune than traditional integral order controllers due to the fractional order terms. One drawback is in determining the optimal parameters for such controller, and research such as [22] - [24] have proposed variants of fractional order controllers using different tuning methods. Unlike PID controllers, which are simple to tune, the current state of tuning fractional order controllers relies on metaheuristic methods.…”

“…All three subsets of intelligent controllers (fuzzy, neural, and others according to [22]) are still researched. For instance, [25], [26] proposed variants of fuzzy PI controllers.…”

Enhancement the Frequency Stability and Protection of Interconnected Microgrid Systems Using Advanced Hybrid Fractional Order Controller

“…[7]. In which, several control schemes from traditional to advanced ones have been proposed for LFC in the literature [8]. The widely-presented LFC schemes are integer order (IO) controls [7], fractional order (FO) controls [2], model predictive controls (MPCs) [9], artificial intelligence (AI) controls [10], fuzzy logic (FL) controls [11], deep learning controls [3], etc.…”

“…From another side, the FO based LFC schemes have proven better performance compared to IO based LFC. Several FO control structures have been proposed in the literature [8], [18]. Their wide expansion is due that they are flexible and have wider freedom in their tuning.…”